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Recommender systems in e-commerce

机译：电子商务中的推荐系统

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Internet is speeding up and modifying the manner in which daily tasks such as online shopping, paying utility bills, watching new movies, communicating, etc., are accomplished. As an example, in older shopping methods, products were mass produced for a single market and audience but that approach is no longer viable. Markets based on long product and development cycles can no longer survive. To stay competitive, markets need to provide different products and services to different customers with different needs. The shift to online shopping has made it incumbent on producers and retailers to customize for customers' needs while providing more options than were possible before. This, however, poses a problem for customers who must now analyze every offering in order to determine what they actually need and will benefit from. To aid customers in this scenario, we discuss about common recommender systems techniques that have been employed and their associated trade-offs.
机译：互联网正在加速并改变完成日常任务的方式，例如在线购物，支付水电费，观看新电影，交流等。例如，在较旧的购物方式中，产品是针对单个市场和受众批量生产的，但这种方式不再可行。基于漫长的产品和开发周期的市场将无法生存。为了保持竞争力，市场需要为具有不同需求的不同客户提供不同的产品和服务。向在线购物的转变使生产商和零售商有责任根据客户的需求进行定制，同时提供比以往更多的选择。但是，这给客户带来了问题，他们现在必须分析每种产品以确定他们的实际需求并从中受益。为了在这种情况下为客户提供帮助，我们讨论了已采用的常见推荐系统技术及其相关的取舍。

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